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87 Publications
- 1 (current)
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2024 | Published | Conference Paper | IST-REx-ID: 19007 | 
A. Kori, F. Locatello, A. Santhirasekaram, F. Toni, B. Glocker, and F. De Sousa Ribeiro, “Identifiable object-centric representation learning via probabilistic slot attention,” in 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Published Version]
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19515 |
M. Fumero, M. Pegoraro, V. Maiorca, F. Locatello, and E. Rodolà, “Latent functional maps: A spectral framework for representation alignment,” in 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Preprint]
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19517 |
D. Crisostomi, M. Fumero, D. Baieri, F. Bernard, and E. Rodolà, “C2M3: Cycle-consistent multi-model merging,” in 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Preprint]
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18996 |
T. Chen, K. Bello, F. Locatello, B. Aragam, and P. K. Ravikumar, “Identifying general mechanism shifts in linear causal representations,” in 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Published Version]
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19005 |
D. Yao, C. J. Muller, and F. Locatello, “Marrying causal representation learning with dynamical systems for science,” in 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Published Version]
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18847 |
R. Cadei, L. Lindorfer, S. Cremer, C. Schmid, and F. Locatello, “Smoke and mirrors in causal downstream tasks,” in ICML 2024 Workshop AI4Science, 2024, vol. 38.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14105 |
S. Sinha, P. Gehler, F. Locatello, and B. Schiele, “TeST: Test-time Self-Training under distribution shift,” in 2023 IEEE/CVF Winter Conference on Applications of Computer Vision, Waikoloa, HI, United States, 2023.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14207 |
S. Löwe, P. Lippe, F. Locatello, and M. Welling, “Rotating features for object discovery,” arXiv. .
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14208 |
Z. Zhu, F. Liu, G. G. Chrysos, F. Locatello, and V. Cevher, “Benign overfitting in deep neural networks under lazy training,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, United States, 2023, vol. 202, pp. 43105–43128.
[Preprint]
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14209 |
M. F. Burg et al., “A data augmentation perspective on diffusion models and retrieval,” arXiv. .
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14210 |
M. Fumero et al., “Leveraging sparse and shared feature activations for disentangled representation learning,” arXiv. .
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14211 |
F. Montagna, N. Noceti, L. Rosasco, K. Zhang, and F. Locatello, “Causal discovery with score matching on additive models with arbitrary noise,” in 2nd Conference on Causal Learning and Reasoning, Tübingen, Germany, 2023.
[Preprint]
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14212 |
F. Montagna, N. Noceti, L. Rosasco, K. Zhang, and F. Locatello, “Scalable causal discovery with score matching,” in 2nd Conference on Causal Learning and Reasoning, Tübingen, Germany, 2023.
[Preprint]
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14214 |
Y. Liu et al., “Causal triplet: An open challenge for intervention-centric causal representation learning,” in 2nd Conference on Causal Learning and Reasoning, Tübingen, Germany, 2023.
[Preprint]
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14217 |
L. Moschella, V. Maiorca, M. Fumero, A. Norelli, F. Locatello, and E. Rodolà, “Relative representations enable zero-shot latent space communication,” in The 11th International Conference on Learning Representations, Kigali, Rwanda, 2023.
[Preprint]
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14218 |
M. Seitzer et al., “Bridging the gap to real-world object-centric learning,” in The 11th International Conference on Learning Representations, Kigali, Rwanda, 2023.
[Preprint]
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14219 |
A. Zadaianchuk, M. Kleindessner, Y. Zhu, F. Locatello, and T. Brox, “Unsupervised semantic segmentation with self-supervised object-centric representations,” in The 11th International Conference on Learning Representations, Kigali, Rwanda, 2023.
[Preprint]
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14222 |
M. Tangemann et al., “Unsupervised object learning via common fate,” in 2nd Conference on Causal Learning and Reasoning, Tübingen, Germany, 2023.
[Preprint]
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14333 |
P. M. Faller, L. C. Vankadara, A. A. Mastakouri, F. Locatello, and D. Janzing, “Self-compatibility: Evaluating causal discovery without ground truth,” arXiv. .
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14948 |
A. Kori, F. Locatello, F. D. S. Ribeiro, F. Toni, and B. Glocker, “Grounded object centric learning,” arXiv. .
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| arXiv
- 1 (current)
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